We use a few cookies

Essential cookies keep the library working. With your permission, we'd also like to use analytics to see what's useful and improve the experience. Read our Privacy Policy or Cookie Policy.

Skip to main content
Home/e-Resources/Medical Sciences/Prevalence and Predictors of elder abuse in Mafikeng Local Municipality in South Africa
PeriodicalsMedical Sciences

Prevalence and Predictors of elder abuse in Mafikeng Local Municipality in South Africa

Checking your access to this record.

Abstract & Overview

Elder abuse is widespread in South Africa and is a serious public health problem. This paper estimated the prevalence and identified the forms and predictors of elder abuse. The paper used cross-sectional data on 506 elderly people from Mafikeng Local Municipality in South Africa, and used the chi-square statistic and the logistic regression model to analyse the data. Overall 64.3% of men and 60.3% of women experienced elder abuse. Physical abuse was more common among men while emotional, financial and sexual abuses were more common among women. Having no working children, being currently single, living in elderly couple family, living in rural areas, having a poor self-perception of health and having a disability were significantly associated with elder abuse. We conclude that the prevalence of elder abuse is high and common, which calls for strategies to prevent the vice.

Cite this record

Paul Bigala, Natal Ayiga (2014). Prevalence and Predictors of elder abuse in Mafikeng Local Municipality in South Africa. African Population Studies, 28(1), 463–463. https://doi.org/10.11564/28-1-500

Copy in another style

Bigala, P., & Ayiga, N. (2014). Prevalence and Predictors of elder abuse in Mafikeng Local Municipality in South Africa. African Population Studies, 28(1), 463–463. https://doi.org/10.11564/28-1-500
Author names are used as deposited, so check their order before you submit.

Metadata is harvested from open-access indexes and can be incomplete. Check a citation against the published version before relying on it — see our open access & attribution policy.